Google BigQuery Integration

Connect Google BigQuery and send data to Google BigQuery with Rudderstack.
DestinationEvent Stream

RudderStack supports sending your event data from a variety of sources to Google BigQuery. Once you add BigQuery as a destination in RudderStack, all your event data is stored into BigQuery buckets periodically. With RudderStack, you don’t have to worry about defining a warehouse schema either – it will take care of everything.

By Integrating BigQuery Support with RudderStack, you can:

  • Directly send your event data from a variety of sources, including web and mobile
  • Load data into BigQuery without having to define a warehouse schema
  • Get the data already transformed and ready for analytics
  • Focus solely getting relevant business insights out of your data rather worrying about storing and retrieving it
Frequently Asked Questions

Google BigQuery is a GCP data warehouse that enables developers to send data from their Data Warehouse.

Difficulty can vary based on your data structure, data cleanliness and required destinations. Many users choose to simplify implementation by sending warehouse data through secure GCP data warehouse integration tools like RudderStack.

Pricing for Google BigQuery can vary depending on your use case and data volume. RudderStack offers transparent, volume-based event pricing. See RudderStack's pricing.

Google BigQuery is a web service offering from Google used for handling and analyzing Big Data. As a part of the Google Cloud Platform, BigQuery allows you to manage large amounts of data and perform real time analysis using SQL-like queries. BigQuery follows the principle of NoOps (No Operations), a concept which implies there is no need for a dedicated team to manage the tool.

Google BigQuery is a managed data warehouse. This means that you can access the data stored in BigQuery by using SQL queries. BigQuery self-manages the storage, encryption, scaling and performance management aspects of your data.

BigQuery is a REST-based web service. It allows you to run complex analytical queries for large amounts of data using SQL. BigQuery is not a substitute for a traditional relational database. It is primarily used for running analytical queries, and not for simple CRUD operations or queries.

BigQuery is built using the Google Dremel paper, which is also an inspiration for other popular tools such as Apache Drill, Apache Impala, and Dremio. Dremel is Google’s distributed system used for interactive querying of large datasets. It is capable of running queries over trillions of rows in seconds.

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About Google BigQuery

Google BigQuery is an industry-leading fully-managed cloud data warehouse that allows you to store and analyze petabytes of data in no time and leverage Google’s machine learning features. RudderStack lets you add Google BigQuery as a destination where you can send your customer event data and params from the data source of your choice., without the pain of detailed setup or custom pipeline development. Setting up a pipeline to BigQuery cloud storage requires a significant amount of detailed engineering work, dealing with googleapis, config files, commands like createdataset and create table and more. With RudderStack, you simply need to set up a service account for authentication in Google Cloud Platform, ensure your IAM profile has the correct permissions and then specify the required details (like projectid). From there, RudderStack will take care of sending data directly to GCP (google-cloud/bigquery), including metadata, without you having to manage a cloud client library, set up a new git workflow in your command line or spend engineering cycles trying to optimize loads. In fact, with RudderStack’s streaming integrations you can even send data to Google in real-time. If you have multiple databases, RudderStack also allows you to send data to relational databases like PostgreSQL, SQL server, mySQL and more.